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Influence and behavior analysis in s...

Alhajj, Reda.

Influence and behavior analysis in social networks and social media

Record Type:	Electronic resources : Monograph/item
Title/Author:	Influence and behavior analysis in social networks and social mediaedited by Mehmet Kaya, Reda Alhajj.
other author:	Kaya, Mehmet.
Published:	Cham :Springer International Publishing :2019.
Description:	vi, 235 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Online social networks.
Online resource:	https://doi.org/10.1007/978-3-030-02592-2
ISBN:	9783030025922$q(electronic bk.)

Influence and behavior analysis in social networks and social media
Influence and behavior analysis in social networks and social media[electronic resource] /edited by Mehmet Kaya, Reda Alhajj. - Cham :Springer International Publishing :2019. - vi, 235 p. :ill., digital ;24 cm. - Lecture notes in social networks,2190-5428. - Lecture notes in social networks..

Social network to improve the educational experience with the deployment of different learning models -- Temporal Model of the Online Customer Review Helpfulness Prediction with Regression Methods -- Traits of Leaders in Movement Initiation:Classification and Identification -- Emotional Valence Shifts and User Behavior on Twitter, Facebook, and YouTube -- Diffusion Algorithms in Multimedia Social Networks: a novel model -- Analyzing Twitter Accounts of Shaw Communications -- Editing Behavior Analysis for Predicting Active and Inactive Users in Wikipedia -- Incentivized Social Sharing: Characteristics and Optimization -- Rumor Source Detection in Finite Graphs with Boundary Effects by Message-passing Algorithms -- Robustness of Influence Maximization against Non-Adversarial Perturbations -- Analyzing Social Book Reading Behavior on Goodreads and how it predicts Amazon Best Sellers.

This timely book focuses on influence and behavior analysis in the broader context of social network applications and social media. Twitter accounts of telecommunications companies are analyzed. Rumor sources in finite graphs with boundary effects by message-passing algorithms are identified. The coherent, state-of-the-art collection of chapters was initially selected based on solid reviews from the IEEE/ACM International Conference on Advances in Social Networks, Analysis, and Mining (ASONAM '17) Chapters were then improved and extended substantially, and the final versions were rigorously reviewed and revised to meet the series standards. Original chapters coming from outside of the meeting round out the coverage. The result will appeal to researchers and students working in social network and social media analysis.

ISBN: 9783030025922$q(electronic bk.)

Standard No.: 10.1007/978-3-030-02592-2doiSubjects--Topical Terms:

281852
Online social networks.

LC Class. No.: HM742 / .I545 2019

Dewey Class. No.: 302.30285

Influence and behavior analysis in social networks and social media
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490 1 $a Lecture notes in social networks, $x 2190-5428
505 0 $a Social network to improve the educational experience with the deployment of different learning models -- Temporal Model of the Online Customer Review Helpfulness Prediction with Regression Methods -- Traits of Leaders in Movement Initiation:Classification and Identification -- Emotional Valence Shifts and User Behavior on Twitter, Facebook, and YouTube -- Diffusion Algorithms in Multimedia Social Networks: a novel model -- Analyzing Twitter Accounts of Shaw Communications -- Editing Behavior Analysis for Predicting Active and Inactive Users in Wikipedia -- Incentivized Social Sharing: Characteristics and Optimization -- Rumor Source Detection in Finite Graphs with Boundary Effects by Message-passing Algorithms -- Robustness of Influence Maximization against Non-Adversarial Perturbations -- Analyzing Social Book Reading Behavior on Goodreads and how it predicts Amazon Best Sellers.
520 $a This timely book focuses on influence and behavior analysis in the broader context of social network applications and social media. Twitter accounts of telecommunications companies are analyzed. Rumor sources in finite graphs with boundary effects by message-passing algorithms are identified. The coherent, state-of-the-art collection of chapters was initially selected based on solid reviews from the IEEE/ACM International Conference on Advances in Social Networks, Analysis, and Mining (ASONAM '17) Chapters were then improved and extended substantially, and the final versions were rigorously reviewed and revised to meet the series standards. Original chapters coming from outside of the meeting round out the coverage. The result will appeal to researchers and students working in social network and social media analysis.
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650 2 4 $a Consumer Behavior. $3 772804
650 2 4 $a Social Media. $3 742054
700 1 $a Kaya, Mehmet. $3 775307
700 1 $a Alhajj, Reda. $3 489480
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